LncRNA-ID

Calculates the coding potential of a transcript using a machine learning model (random forest) based on multiple features including sequence characteristics of putative open reading frames, translation scores based on ribosomal coverage, and conservation against characterized protein families. LncRNA-ID competes favorably with existing coding potential computation tools in lncRNA identification.

Maintainer

Publication for LncRNA-ID

LncRNA-ID citations

(2)

library_books

PlantRNA_Sniffer: A SVM Based Workflow to Predict Long Intergenic Non Coding RNAs in Plants

2017

Noncoding RNA

PMCID: 5831995

PMID: 29657283

DOI: 10.3390/ncrna3010011

[…] to ncRNAs, if they have not been recorded in the protein databases. PSoL [], SnoReport [], RNAsnoop [], and SnoStrip [] are methods designed to classify small ncRNAs. LncRScan-SVM [], lncRNA-MFDL [], lncRNA-ID [], lncRNApred [], PLEK [], and CNCI [] are methods that use machine learning techniques in order to classify lncRNAs. In particular, ISeeRNA [] and linc-SF [] use machine learning technique […]

[…] ws the longest time to finish the process because of its alignment process. When being tested on a dataset containing 4,000 protein-coding and 4,000 long noncoding transcripts, CPAT takes 35.36 s and LncRNA-ID takes 65.35 s to accomplish the discrimination while PLEK and CPC need 21.47 m and 86.51 h, respectively []. PLEK is 8 times and 244 times faster than CNCI and CPC, respectively, on the same […]